#将 pe.require_grad 设置为 False,以确保反向传播时不会计算 pe 的梯度。 # 创建一个与 pe 相同维度的张量 position,其中包含从 0 到 max_len-1 的数字。 # 创建一个与 pe 相同维度的张量 div_term,其中包含 -(math.log(10000.0) / d_model) 的幂次。 #将 pe 中每两个相邻的元素设置为 position...
2. 5.Convnet作为固定特征提取器,只训练最后一层,通过require_grad=False冻结resnet18的早期层 model_conv = torchvision.models.resnet18(pretrained=True) for param in model_conv.parameters(): param.requires_grad = False # Parameters of newly constructed modules have requires_grad=True by default num...
4 self.matmul = MatMul(set_strategy={[1, 1], [1, 4]}) 5 self.W = Parameter(Tensor(shape), require_grad=True) 6 def construct(self, X): 7 Y = self.bn(X) 8 Z = self.matmul(y, self.W) 9 return Z MindSpore 较灵活,它支持用户指定的高级策略配置,称之为半自动并行(semi-auto-...
@@ -959,6 +960,7 @@ REGISTER_OP_CPU_KERNEL(matmul_grad_grad, #ifdefined(PADDLE_WITH_HIP) REGISTER_OP_CUDA_KERNEL( matmul, ops::MatMulKernel<phi::GPUContext,int8_t>, Copy link Contributor SylarTiaNIIJun 24, 2024 量化相关的kernel可以拆分到推理的PR里面。
), f"try to merge gradient not belong to current shard: [{grad_name}]" persistable_grad_name = grad_name + '@GradiantMerge' persistable_grad_name = grad_name + '@GradientMerge' assert ( grad_name not in self._grad2merged_grad ), "grad [{}] already in grad2merged_grad, maybe ...
在本案例中以权威的语义匹配数据集LCQMC为例,LCQMC数据集是基于百度知道相似问题推荐构造的通问句语义匹配数据集。训练集中的每两段文本都会被标记为 1(语义相似) 或者 0(语义不相似)。更多数据集可访问千言获取哦。 例如百度知道场景下,用户搜索一个问题,模型会计算这个问题与候选问题是否语义相似,语义匹配模型会找...
Also, Johns Hopkins was a tremendously supportive institution with respect to money and people's time in grad school. Blind spots still exist for all institutions. I hope to add comments on what institutions could make this easier or information on how students can help themselves (as many may...
paddle.no_grad=paddle.fluid.dygraph.base.no_grad_ 3 changes: 0 additions & 3 deletions 3 docs/api/api_label Original file line numberDiff line numberDiff line change @@ -91,12 +91,10 @@ paddle.fluid.framework.is_compiled_with_xpu .. _api_paddle_fluid_framework_is_co paddle.fluid...
WaveGrad DiffWave Motivations of GAN-based vocoders: Modeling speech signals by estimating probability distribution usually has high requirements for the expression ability of the model itself. In addition, specific assumptions need to be made about the distribution of waveforms. Although autoregressive ne...
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署) - Paddle/python/paddle/distributed/parallel.py at release/3.0-beta · PaddlePaddle/Paddle